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Is it possible to run multiple regressions with multiple IVs?
I do have a latent variable (motives) with 3 subscales (egoistic, altruistic and biospheric, level: metric) as predictors and a latent variable with 4 subscales as a second predictor (moderator). The outcome or dependent variable is metric. 1) Is it possible to run multiple regressions in that case?
How is the suppression effect introduced in regression?
Strong suppression is typically introduced consciously. A researcher seeks for a characteristic which must correlate with the DV as weak as possible and at the same time would correlate with something in the IV of interest which is considered irrelevant, prediction-void, in respect to the DV.
Why does a suppressor raise the observed R-square?
Suppressor is the independent variable which, when added to the model, raises observed R-square mostly due to its accounting for the residuals left by the model without it, and not due to its own association with the DV (which is comparatively weak).
What is the difference between moderator and suppressor?
Moderator: IV which, varying, manages the strength of the effect of another IV on the DV. Statistically, it is known as interaction between the two IVs. Suppressor: IV (a mediator or a moderator conceptually) which inclusion strengthens the effect of another IV on the DV.
Can a regression be used to control for smoking?
After they included smoking in the model, the regression results indicated that coffee intake lowers the risk of mortality while smoking increases it. This model isolates the role of each variable while holding the other variable constant. You can assess the effect of coffee intake while controlling for smoking.
What happens when you omit a variable in a regression?
Omitting an important variable causes it to be uncontrolled, and it can bias the results for the variables that you do include in the model. This warning is particularly applicable for observational studies where the effects of omitted variables might be unbalanced.
How to choose the correct type of regression analysis?
There are numerous types of regression models that you can use. This choice often depends on the kind of data you have for the dependent variable and the type of model that provides the best fit. In this post, I cover the more common types of regression analyses and how to decide which one is right for your data.